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Computer Vision – ECCV 2024 : 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part LVI / edited by Aleš Leonardis, Elisa Ricci, Stefan Roth, Olga Russakovsky, Torsten Sattler, Gül Varol.
Springer Nature - Springer Computer Science (R0) eBooks 2025 English International Available online
View online- Format:
- Book
- Author/Creator:
- Leonardis, Aleš.
- Series:
- Lecture Notes in Computer Science, 1611-3349 ; 15114
- Language:
- English
- Subjects (All):
- Image processing--Digital techniques.
- Image processing.
- Computer vision.
- Computer networks.
- Machine learning.
- Computers, Special purpose.
- User interfaces (Computer systems).
- Human-computer interaction.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Image Processing.
- Computer Communication Networks.
- Machine Learning.
- Special Purpose and Application-Based Systems.
- User Interfaces and Human Computer Interaction.
- Local Subjects:
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Image Processing.
- Computer Communication Networks.
- Machine Learning.
- Special Purpose and Application-Based Systems.
- User Interfaces and Human Computer Interaction.
- Physical Description:
- 1 online resource (583 pages)
- Edition:
- 1st ed. 2025.
- Place of Publication:
- Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
- Summary:
- The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024. The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; motion estimation.
- Contents:
- HowToCaption: Prompting LLMs to Transform Video Annotations at Scale
- LabelDistill: Label-guided Cross-modal Knowledge Distillation for Camera-based 3D Object Detection
- Beyond the Data Imbalance: Employing the Heterogeneous Datasets for Vehicle Maneuver Prediction
- On Pretraining Data Diversity for Self-Supervised Learning
- Look Around and Learn: Self-Training Object Detection by Exploration
- Bayesian Self-Training for Semi-Supervised 3D Segmentation
- Motion and Structure from Event-based Normal Flow
- ParCo: Part-Coordinating Text-to-Motion Synthesis
- Learning to Complement and to Defer to Multiple Users
- Tiny Models are the Computational Saver for Large Models
- DragVideo: Interactive Drag-style Video Editing
- Multi-Sentence Grounding for Long-term Instructional Video
- Do Generalised Classifiers really work on Human Drawn Sketches?
- KMTalk: Speech-Driven 3D Facial Animation with Key Motion Embedding
- Head360: Learning a Parametric 3D Full-Head for Free-View Synthesis in 360°
- MotionDirector: Motion Customization of Text-to-Video Diffusion Models
- Text2LiDAR: Text-guided LiDAR Point Clouds Generation via Equirectangular Transformer
- Enhanced Motion Forecasting with Visual Relation Reasoning
- Rate-Distortion-Cognition Controllable Versatile Neural Image Compression
- Temporal As a Plugin: Unsupervised Video Denoising with Pre-Trained Image Denoisers
- LiDAR-based All-weather 3D Object Detection via Prompting and Distilling 4D Radar
- MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models
- Post-training Quantization with Progressive Calibration and Activation Relaxing for Text-to-Image Diffusion Models
- Scene Coordinate Reconstruction: Posing of Image Collections via Incremental Learning of a Relocalizer
- Diffusion Models are Geometry Critics: Single Image 3D Editing Using Pre-Trained Diffusion Priors
- Weakly Supervised Co-training with Swapping Assignments for Semantic Segmentation
- StoryImager: A Unified and Efficient Framework for Coherent Story Visualization and Completion.
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 3-031-72992-7
- OCLC:
- 1465266492
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